Making Inference Across Mobilization and Influence Research:
Comparing Top-Down and Bottom-Up Mapping of Interest Systems
Joost Berkhout
Department of Political Science
University of Amsterdam
Jan Beyers
Department of Political Science
University of Antwerp
Caelesta Braun
Department of Political Science
Free University of Amsterdam
Marcel Hanegraaff
Department of Political Science
University of Antwerp
David Lowery
Department of Political Science
Pennsylvania State University
This paper was prepared for Presentation at the ECPR General Conference in Glasgow,
2014
Abstract
Students of mobilization and influence employ two quite different approaches to
mapping interest systems. The first typically rely on a bottom-up mapping strategy in
order to identify the total size and composition of the interest community. In contrast,
students of influence have typically relied on a top-down mapping strategy in which the
mapping of politically active organizations depends on samples of specific policy issues,
usually those that are most prominent on policy agendas. But each domain of research
also routinely uses data gathered to address research questions on mobilization or
influence. How valid is this cross-domain use of large-n data on the politics of interest
representation? In other words, are inferences based on a top-down mapping strategy
generalizable to an interest system as whole and vice-versa? We address this question
using unique datasets drawn from the INTEREURO project’s analysis of lobbying in the
European Union (EU), datasets that employs both mapping strategies. Although, our
analysis does not produce one simple answer to the question of comparability, our
evidence shows that bottom-up and top-down sampling are considerably compatible
and equivalent. We consider why this might be so and what research is needed to more
fully assess the validity of cross-domain use of data generated from the two sampling
strategies.
Making Inference Across Mobilization and Influence Research:
Comparing Top-Down and Bottom-Up Mapping of Interest Systems
For most of the history of scholarship on the politics of interest representation,
research was largely confined to only one or a few interest organizations. The reasons
for this were obviously a lack of data on larger populations of organizations and their
lobbying activities. Some notable scholarship was generated from this early empirical
work, and it remains relevant to our understanding of interest politics to this day
(Witko, in press). Still, following the strong advice of Baumgartner and Leech in their
1998 work, Basic Interests, the last two decades have seen a flowering of large-n
research on interest organizations (see reviews in: Beyers et al. 2008; Bunea and
Baumgartner 2014; Hojnacki et al 2013). Students of mobilization and influence have
adopted research strategies that entail the mapping of large numbers of interest
organizations active in politics and public policy so as to more fully account for the
important contextual forces that govern both mobilization and influence.1
Students of mobilization and influence have, however, employed two quite
different approaches to mapping interest systems. This is not surprising in that they are
addressing somewhat different questions. The former are interested in who enters and
leaves interest communities and the processes that govern their density and diversity.
Answering such questions requires that we have a census of the total interest systems
across time and/or space. Thus, mobilization scholars have typically relied on a bottomup mapping strategy in order to identify the total size and composition of the entire
interest community. An early example of such research is Gray and Lowery’s (1996)
analysis of U.S. state lobbying registration rolls in The Population Ecology of Interest
1
Please note that with ‘mobilization’ and ‘influence’ we refer to studies on research questions pertaining
to, on the first, both mobilization (i.e the formation of a group and the decisions by existing organizations
to become politically active) and organizational populations, and, on the latter, both political strategies
and influence on public policy. We use these terms in a somewhat broader sense than elsewhere (e.g. Gray
and Lowery 2004).
1
Representation. A bottom-up mapping strategy usually involves drawing samples from
general registries of politically active organized interests, such as the U.S. state lobby
registration rolls. In contrast, influence scholars are ultimately interested in how policy
processes unfold, more precisely whether and how organized interests influence
political and policy decisions. Addressing these questions requires that we attend first
to the actual policy outcomes policymakers produce. Accordingly, students of influence
have typically relied on a top-down mapping strategy in which samples of interest
organizations are drawn from those active on specific policy issues, typically those that
are most prominent on policy agendas. Perhaps the earliest example of such research is
Heinz et al. (1993) analysis of the interests active in four prominent policy domains in
the U.S. in The Hollow Core (recent examples are: Baumgartner et al. (2009), Beyers et
al. (2014a, 2014b) and Mahoney (2008)). Importantly, neither mapping strategy in the
now burgeoning literature relying on large-n research is more valid in and of itself; each
is appropriate for its distinctive purpose of examining issues of mobilization or influence
(Beyers et al. 2014b).
Still, interest representation scholarship is not neatly divided between those who
study influence and those who study mobilization. Students of each also routinely use
data gathered to address issues of either mobilization or influence to address questions
about issues better associated with the other. For example, in Interest Groups and
Health Care Reform Across the United States, Gray, Lowery, and Benz (2013) employ
data on the diversity of interests on U.S. state lobby registration rolls to assess their
influence on the adoption of three health policies, implicitly assuming that the diversity
of total lobby registrations is isomorphic with the diversity of interests actually lobbying
on the policies. Similarly, while Klüver’s Lobbying in the European Union, is largely
devoted to the analysis of influence based on a sample of organization submissions on
2
proposals under consideration by the European Commission (EC), it also addresses
broader issue of mobilization and the diversity of the EU interest system (2013, 138144) using the same data. Extracting broader generalizations on these latter questions
from data on the explicit activities of organized interests requires, of course, an
assumption that the diversity of interests active on a sample of on-going policy decisions
map in an isomorphic manner on the diversity of the larger interest system. Clearly,
then, it is not uncommon for data gathered via one mapping strategy and designed to
test hypotheses about either mobilization or influence to be used to say something
about issues more appropriately in the other domain.
How valid is this cross-domain use of large-n data on the politics of interest
representation? Can data gathered on the diversity of interest organizations from a
bottom-up mapping of the full interest population be validly employed to address issues
of influence on important political and policy decisions? And should we be concerned
about the use of data gathered on the lobbying activities of organized interests on a
sample of important issues to tell us something about overall patterns of mobilization
within political systems? We address these questions using data drawn from the
INTEREURO project’s analysis of lobbying in the EU (Beyers et al. 2014), a project that
employed both mapping strategies. We first outline the many reasons to suspect that
the two mapping strategies should indeed generate quite different distributions of
interest organizations. Then, we compare the distributions of interests generated by the
two INTEREURO sampling strategies across six variables generated for both: the level of
mobilization of the organization, their organization structures, the geographic location
of their headquarters, the type of actor they are, and either the economic or social sector
from which they are drawn. In a second empirical portion of the paper, we assess the
degree of overlap in the two mapping strategies in terms of identifying individual
3
interest organizations. Importantly, although our analysis does not produce one simple
answer to the question of comparability, our evidence shows that bottom-up and topdown sampling are considerably compatible and equivalent. In the conclusion, we
consider why this might be so and what research is needed to more fully assess the
validity of cross-domain use of data generated from the two sampling strategies.
The Case for Incongruence in Mapping Strategies
As noted earlier, scholarship on the politics of interest representation is not so
neatly divided between those interested in mobilization and those concerned about
influence. Many scholars routinely move between the domains, and often bring their
data with them. But to better understand why such cross-use of data generated from the
two mapping strategies might be of concern, we might adopt a hard critical stance from
one or the other domain and assess why it is problematic to employ data generated from
the preferred mapping strategy employed by the other domain.
There are several reasons why students primarily interested in mobilization
might be concerned about comments made on those topics by scholars using mostly
data generated from top-down samples of organizations considered either most active
in general or most active on a sample of on-going and often important issues before a
government of the type employed by Heinz (1993), Klüver (2013), Yackee (2006),
Beyers et al. (2014b), Mahoney (2008) and Baumgartner et al. (2009). First, and
perhaps most importantly, a focus on policy decisions is simply besides the point from
the perspective of many scholars given that organizations might mobilize (i.e. develop
political activities or monitoring the policy process) for any number of reasons beyond
actually seeking influence on specific policy choices. Indeed, joining a lobbying
community may be more about mobilizing members or securing finance than about
4
policy influence per se (Baumgartner et al 2009; Braun 2014; Lowery 2007; Hanegraaff
2014). Attending to these concerns may lead to little or no explicit effort to actually
influence policy decisions, and organizations motivated by such concerns would be
missed or at least underrepresented in samples drawn from those actively seeking
influence on specific policy decisions.
Second, even when organized interests are primarily concerned about influencing
public policy, the policy process is a long and winding one, running from efforts to get
any kind of hearing to final and authoritative policy choices on concrete proposals. And
importantly, most interest organizations fail to even get their preferred issues on the
table (Baumgartner et al. 2009). Such organizations would be absent from samples
generated using a top-down strategy since these are typically attentive to lobbying
activity on issues that have already secured space on the policy agenda in their form of a
concrete policy proposal. Thus, active proposals are likely a biased sample of all issues
considered by policy makers, and this, in turn, is likely to generate a biased sample of
interest organizations compared to all who might be seeking policy change. Indeed, topdown mapping often assumes, if implicitly, that such activity is in response to demand
function generated by the introduction of a proposal (Leech et al. 2005). The
inadequacy of this assumption is fully evident in lobbying in the EU where there is no
clear pattern in the timing of the appearance of a specific policy proposal and lobbying
activity by interest organizations (Toshkov et al. 2013). Much of lobbying – if often
unsuccessful – occurs long before a specific proposal appears on policy agendas, which
suggests that samples of interest organizations drawn from lobbying activity on specific
and often important policy proposals may miss a great deal of lobbying and many
5
interest organizations.2
Third, to mobilization scholars, lobbying involves much more than trying to
secure a yes or no vote on a policy proposal. Indeed, much of “lobbying” is merely
occasional policy monitoring or dipping into the policy process on only an episodic
basis. Indeed, interest communities are highly dynamic, with many organizations
appearing only occasionally and then disappearing from the interest population
(Berkhout & Lowery 2011; Anderson et al. 2004). But this research has also shown that
interest communities tend to have a number of persistent members – the “old bulls” that
are routinely present within interest systems. It would seem plausible that such “old
bulls” or “permanent residents” are overrepresented in samples generated from topdown mapping strategies and that the “mayflies” or “tourists” are seriously
underrepresented, as are those who engaged in only more passive forms of policy
monitoring. Yet, students of mobilization, given their concerns about patterns of exit
from and entry into interest communities are as equally attentive to both the old bulls
and the mayflies; each is equally relevant to assessing the degree to which interest
systems are open and unbiased. But a sample based on influence activity at the final
stage of the policy process may miss many of the latter.
And fourth, there is a long history of suspicion of bias in interest systems in
research on interest representation. Interest systems are often viewed as overrepresenting a few large interests, typically business interests (Schattschneider 1960;
Schlozman et al. 2012). The diversity of interest communities is, of course, a major topic
of concern to mobilization scholars. But there is also an implicit assumption in the
2
Some top-down samples (like that generated by Baumgartner et al. 2009) are somewhat less subject to
this problem given that they start with the proposals organizations are working on rather than sampling
interest organizations from those working on important issues at the final stage of the policy process. Also
the INTEREURO-project addresses this issue by adopting a stratified sampling strategy which ensures that
both salient and less salient issues are included in the study (see below).
6
literature that interest communities may become even more biased as policy proposals
move toward final decisions. That is, contrary voices, through a process that might be
labeled an iron law of influence concentration, may become increasingly less active,
have less access, and have less influence as proposals move through the policy process,
and the scope of the conflict becomes narrower. As noted by Schattschneider (1960, 34)
‘scope and bias are aspects of the same tendency’, and the narrower the scope of conflict,
the stronger the bias of the interests involved. From the perspective of mobilization
scholars, the potential of increasingly less access is especially problematic. If interest
systems become more concentrated and biased as a proposal moves through the policy
process, then samples drawn via top-down mapping may exclude many organized
interests with a legitimate interest in a policy proposal.3 In sum, then, there are many
reasons for mobilization scholars to suspect that data generated by top-down mapping
provides a valid sample of interest organizations that can be used to address
mobilization-related questions.
Conversely, there are several reasons why students primarily interested in
influence might be suspicious of comments made on that topic by scholars using data
generated from bottom-up samples of organizations based on lobby registration rolls or
some other census of the entire lobbying community of the type employed by Gray and
Lowery (1996); Gray et al. (2013), Mahoney (2008), Hanegraaff (2014), Halpin and
Binderkrantz (2011), Berkhout (2010), and Poppelaars (2009a;b). Many of these are
the obverses of those raised against using top-down samples by mobilization scholars.
That is, if the focus is really on the influence of organized interests on final policy
3
This Schattschneiderian expectation (the further along the policy process, the narrower the scope of
conflict, the lower the diversity) runs counter, of course, to the other Schattschneiderian hypothesis that
the scope of conflict is expanded in the process from agenda-setting onwards and through the
involvement of public authority and, most notably, ‘public conflicts’ in the legislature (Schattschneider
1960, 40).
7
decisions, then those organizations lobby for some other reason than securing influence
– the “visitors” or “mayflies”, those denied any real access to decision makers, and those
who fail to get their proposals on the policy agenda – are less relevant for analyzing how
concrete policy processes unfold. Thus, data from samples generated from a bottom-up
sampling strategy may be contaminated with the counting of many interest
organizations that either not seeking influence or are prevented from doing so.
How plausible is such contamination? On first face, it would seem to be
significant. It seems likely, for example, that the activities of membership groups and
non-profits are more heavily motivated by concerns of mobilization and finance than are
institutions. This implies that such organizations would be over-represented in bottomup samples, but less visible in top-down samples. It also seems that large businesses and
business associations would be more likely to maintain a constant presence in lobbying
communities – and be part of the set of “permanent residents” – than smaller business
interests. It seems plausible – at least from a Schattschneiderian perspective in which
‘pressure politics is a selective process ill designed to serve diffuse interests’ (1960, 35)
– that access to policymakers during the final decision-stage is easier to obtain for
wealthy business interests than for NGOs and other public interest groups; they are
more likely among the “old bulls”. And if the policy proposals of some types of
organizations receive a more ready hearing and, thus, space on the policy agenda than
those of others (Schlozman et al. 2012), then the distributions of organizations at the
table when making authoritative decisions on public policy may be skewed. It seems,
then, that is plenty of reason to suspect the data generated from a bottom-up census of
the interest population will represent a biased and unrealistic representation of those
truly active at the final stage of the policy process.
But even if the distribution of interest organizations generated via a top-down
8
sample of active interest organization faithfully mirrored those produced via a bottomup census of interest organizations, there remains a more serious problem for influence
research relying a bottom-up census of interest organizations. This problem, if not
perhaps an inherent one, lies in the nature of the data typically generated by the two
research strategies. That is, because bottom-up research strategies typically attempt to
map whole interest communities, they are severely limited in assessing the amounts or
kinds of activities organizations undertake beyond merely showing up somewhere in
the policy process. To use such census data to study influence, one has to basically
assume that all interest organizations do more or less the same thing once present. In
contrast, top-down samples, because they work with a smaller sample of issues,
typically do much more than merely registering presence or absence in the policy arena.
They assess lobbying strategies and tactics, evaluate comments and statements used to
frame choices, and, among many other things, look at the frequency and locus of explicit
lobby activity. These kinds of data allow scholars to weigh interest organizations in
terms of the intensity of their efforts to influence decisions, something that cannot be
done with a simple count of interest organizations. For these reasons, it would seem
doubtful that a census of organized interests used for mobilization research could
validly serve as a quick and ready substitute for a top-down sample.
Is, then, the prospect of cross-domain use of datasets generated using top-down
and bottom-up generated lists of interest organizations really so bleak in terms of
inferential validity as the preceding arguments suggest? Perhaps not. Despite their
many differences, most interest organizations employ a fairly standard, common
repertoire of activities once they join interest communities (Walker 1991; Baumgartner
et al. 2009, 149-150). This implies that weights are not needed for levels or intensity of
lobbying by organized interests. And given the high frequency of entry into both U.S.
9
and European interest systems (Berkhout and Lowery 2011; Anderson et al. 2004), both
systems remain fairly open to participation on the part of interest organizations of all
types. Indeed, there is in the end nearly always two sides to policy debates, thereby
insuring that one type of interests does not fully dominate policy discussions
(Baumgartner et al. 2009). Further, prior research suggests the vast bulk of lobbying is
done on only a few proposals considered by governments (Baumgartner & Leech 2001;
Halpin 2011; De Bruycker & Beyers 2014). If this is true, then a top-down sample of
interests active on a sample of major proposals should be similar to one drawn from the
full interest population. And perhaps most importantly of all, research on influence
topics using bottom-up or population-level data on interest organizations has not
generated findings notably different from those relying on a true top-down sample of
interest organization activity, and research on mobilization questions based on a topdown sample of active interest organizations has not produced findings that are
discernibly different from those using a bottom-up census. For instance, relying on nonissue focused samples Binderkrantz and colleagues (2014) demonstrate that interest
group strategies are broadly consistent with studies using policy-centred samples. Still,
we cannot know if this is a happy accident or if it masks a more fundamental inference
problem given that there is to date no research that has simultaneously employed both
types of data so that we can meaningfully compare the descriptions of a common
interest community.
Comparing the Two Research Strategies
We provide such a comparison in the remainder of this paper. Our data were
generated from the INTEREURO Project (Beyers et al. 2014a; 2014b), which employed
10
both types of mapping strategies in its analysis of lobbying in the EU.4 We first describe
the two mapping strategies and the data. We then turn to looking at both the overall
distributions of organizations generated by each on six variables and the overlap in the
individual organizations identified via each strategy.
The INTEREURO Bottom Up Mapping
The ideal bottom-up data source includes all organizations in a given polity that
engage with public policy. In conceptual terms, each organization showing some activity
in relation to the policy process is defined as interest organization, including individual
institutions such as banks, hospitals or regional authorities. An interest organization
enters the population when it shows such an activity and exits the population when it is
no longer politically active in the polity under study. Remember that ‘political interest’ is
commonly part of any definition of ‘interest groups’ (e.g. Beyers et al. 2008; Salisbury,
1994). Here we employ a behavioral definition of interest organizations rather than an
organizational-structural one. In the latter, and in contrast to our approach, a bottom-up
population would exclude individual institutions but include all collective, non-party
organizations with ‘political’ goals, regardless of whether these goals are observably
articulated in the policy process (see discussion in: Halpin & Jordan 2012, Jordan et al.
2004).
The organizations in the doorpass register of the European Parliament (EP)
between 2008 and 2010 form our bottom-up population.5 The EP issues entry passes to
persons who wish to enter the Parliamentary premises frequently and engage in
4
The INTEREURO data are or will shortly be available at www.intereuro.eu.
The list includes data on 23012 entry passes of persons affiliated to 3704 different organizations and
was provided by the Parliamentary Information Systems Unit (SIP) of the EP in May 2011. The earliest
passes in that version are from early 2004 and the newest are from April 2011. The list is governed by
Rules of Procedure of the EP (Title 1, Chapter 1, Rule 11, 5-11, also see Annex IX).
5
11
activities ‘carried out with the objective of directly or indirectly influencing the
formulation or implementation of policy and the decision-making processes of the EU
institutions’ (EP rules, Annex IX(8)). Entry passes are valid for one year and may be
renewed. This ensures that data is relatively up-to-date. We take a two-year time period
in order to match the bottom-up generated population with the top-down generated
population based on policy proposals drawn from the period 2008-2010, see below. The
precise rules governing the issuing of passes have remained relatively constant over the
time period studied (but note that, for instance, the introduction ‘express’ passes mid2006 led to a decline in the aggregate number of passes).
We have several reasons for relying on this register rather than other data
sources. First, in the context of the EU institutions, the EP is designed to be the most
open to organized interests. In the end, it is the role of Members of the European
Parliament (MEPs) to represent interests and political positions. They consequently
have a reason to converse with various organized interests, and, in light of the
importance of legislative decisions, various interest groups also would like their views
heard by MEPs. The EP compared with the EC and Council should have the lowest
threshold of policy participation for interest groups and it shows at least some openness
regarding these practices, as noted by Balme and Chabanet (2008 216) ‘the creation of a
system of regulation and supervision of lobbying bespeaks of a political will (…) specific
to the European Parliament’. The consultations of the EC have a similarly low threshold
of participation but only occur on specific, and certainly not all, proposals. Organizations
with some interest in EU policies are likely to, at some point over a longer time period,
want to, and are welcome to, enter the building of the EP. This makes the register is a
good bottom-up population data source compared to data sources (for instance those
associated with other EU institutions or published by private companies)..
12
Second, registers of this type are common in interest representation studies. The
register of the EP itself has previously been used for various research purposes
(Toshkov et al. 2012, Wonka et al. 2010). The use of lobby registers is also relatively
common outside the EU case. Most notably, Gray and Lowery state that in the US case
‘the most valid indicator of broadscale political activity now available is provided by
lobby registration rolls’ (Gray & Lowery 1996, 7). The Lobbyistenregister of the German
Bundestag has been used for several surveys (Dür & Mateo 2013, 679, Jentges et al.
2012, Klüver 2012). Even though the precise requirements vary per institution, the
common usage of such registers still provides some confidence in the relative quality of
the data.
Third, alternative data sources are however not better. To start, the
Transparancy Register (or ‘Register of Interest Representatives’), in place as successor
of the official list of the EC (CONECCS) since mid-2009 and as joint EC-EP list since 2011,
only very recently reached a level of coverage that makes it potentially useful for
academic purposes. The time-period consequently does not match with our top-down
population data. The EP register, in place since 1996 (of which we cover 2008-2010),
runs over a longer time period, and most importantly during the time period in which
we select organizations based on the top-down sampling strategy. Further note that
currently all organizations in the EP register are expected, when possible, to register in
the Transparency Register.6 By using the EP list we effective rely on a sub-sample of the
6
But note that there may be a number of organizations in the EP list that are not in the Transparency
register because of the ‘scope conditions’ of the latter. EP administrators have quite some leeway in
issuing badges: ‘Rule 11 (5) states: Such badges may be issued to: - persons whose names appear in the
transparency register or who represent or work for organizations whose names appear therein, although
registration shall not confer an automatic right to such a badge;- persons who wish to enter Parliament’s
premises frequently, but who do not fall within the scope of the agreement on the establishment of a
transparency register(3); - Members’ local assistants and persons assisting Members of the European
Economic and Social Committee and the Committee of the Regions.’ Transparency campaign groups, most
notably ALTER-EU, are especially concerned about the exclusion of various types of legal advice, for
instance, Annex IX, 10(a) excludes from the register any ‘company and its advisers [who]are involved as a
13
Transparency Register. This is in line with the advice of Greenwood and Dreger (2013,
159) that ‘for research use’ a selection filter is needed ‘to make the data less prone to
quirky outliers’.7 Greenwood and Dreger (2013, 150) note that in January 2013 1179 out
of 5494 organizations from the Transparancy Register hold access passes to the EP. The
overlap between our EP register data and the Transparency register is likely to be
bigger because we rely on a two-year period rather than a snapshot. EP passholdership
is also likely to distribute relatively evenly over categories of registration in the
Transparency register. That is, Greenwood and Dreger (2013, 149, 152) report only a
somewhat larger proportion of EP passholders among business associations (19%) than
among non-governmental organizations (15%).8
Another alternative data source would be any one of the several public affairs
directories. These, most notably the European Public Affairs Directory published by
Landmarks (since 2011 Dod’s), have been used in a couple studies (e.g. Sorurbakhsh
2014; Berkhout & Lowery 2010; Wonka et al. 2011). Such commercial directories are
marketed to the ‘Brussels community’ of policy makers, stakeholders and civil servants.
Their registration practices seem to favor interests with permanent and relatively
central presence in Brussels and that are ‘collectively’ organized. At the same time, such
directories seek the broadest possible coverage to market the large number of entries in
party in a specific legal or administrative case or proceeding, any activity relating directly thereto which
does not seek as such to change the existing legal framework’.
7 Please note that they recommend to select only organizations with a ‘European interest’ or a Brussels
address. As said, the main benefit of the EP pass criterion is that it indicates policy engagement.
8 Greenwood and Dreger (2013, 149-152) find the following distribution of EP passholders across the
registration categories:
Transparency Register category
n
passholders
(I) Professional consultancies/law firms/self-employed consultants
(II) In-house lobbyists and trade/professional associations
(III) Non-governmental organizations
(IV) Think tanks, research and academic institutions
(V) Organizations representing churches and religious communities
(VI) Organizations representing local, regional and municipal authorities, and other
public authorities
14
124
541
193
36
10
47
N in
Transparancy
Register
620
2816
1304
411
37
306
%
20%
19%
15%
9%
27%
15%
their directory (see Berkhout & Lowery 2008).
We do not use any of these directories because the time period reliably covered
does not match the time period of our top-down sample. That is, around 2010 the
European Public Affairs Directory was just ‘in transition’ between the publishers
Landmarks and Dod’s. Other directories, such as stakeholder.eu, the Europa-OECKL or
Euroconfidentiel, were not yet in print (or just out of print). Previous studies show some
overlap between Landmarks and EP register: Wonka et al. (2010, 466) removed 487
organizations as duplicates arising from the addition of the EP register (n=1534, version
April 2008) to the combined CONECCS-Landmarks list (CONECCS: n=749, Landmarks:
n=2522, overlap: n=489). The inclusion of organizations of the EP register over a longer
time-period, as we do, is very likely to produce a larger overlap with the Landmarks PA
directory. However, there probably remains a substantial set of organizations that
appears in the Public Affairs Directory but not in the EP register, even over the longer
term because the PA directory also lists organizations that take a more distant approach
to policy activities and are mainly working on ‘interest aggregation’ activities such as
annual conferences, networking among member-associations and so on. Such
organizations may never lobby the EP. Future studies probably benefit from combining
the EP register data with directories such as the Public Affairs directory or the
Transparency Register.
The INTEREURO Top Down Mapping
The starting point for the INTEREURO top-down mapping was a list of all
proposals for generally binding EU law, i.e. directives (N=144) and regulations (N=459),
adopted by the EC between 1 January 2008 and 31 December 2010 (Beyers et al.
2014a). One reason for selecting a particular time slot was to maximize the chance of
15
finding interview partners in the Commission as well as among organized interests. We
also wanted to be reasonably certain that at the time when we did our interviews a
decision would have been taken on the proposal (so no proposals that were too recent
could be included; see also Beyers et al. 2014c). After eliminating a few proposals
concerning the remuneration of and/or pensions for Commission officials, the internal
management of the EU institutions and codification proposals, the list contained 111
proposals for directives and 427 proposals for regulations.9
Importantly is that we stratified the sample of legislative proposals according to
public saliency, which increased the likelihood to sample highly salient cases. We did
this by checking the media coverage of all proposals in five sources, namely Agence
Europe, European Voice, the Financial Times, the Frankfurter Allgemeine Zeitung, and Le
Monde. About two thirds of the proposals for directives and sixty per cent of the
proposals for regulations were mentioned in at least one media source. We found most
media hits in Agence Europe, and fewest hits in Le Monde. The resulting sample includes
48 proposals for directives and 38 proposals for regulations that were mentioned in at
least two of these media sources. We opted for this rather low threshold of two media
hits in order to allow for a substantial variation in salience across proposals in the
sample. Moreover, to add additional variation in terms of salience, we added a randomly
selected set of ten proposals for directives and nine proposals for regulations that did
not meet the media coverage criterion. Finally, we added all proposals for directives and
regulations that had not made it into the sample following our strategy, but for which
public consultations had been held and consultation documents are available (Klüver et
9
We decided to sample directives and regulations separately, as a simple random sample would have
made us select very few directives (about four regulations for each directive). Having a large enough
number of directives in the sample was important as we wanted to see whether there are any differences
in terms of lobbying between regulations and directives, and because for directives we can also study
lobbying during the national transposition process.
16
al. 2014). We did this for pragmatic reasons, as we wanted to benefit from the additional
data that is available for consultation cases.
This process resulted in a sample of 125 proposals, which breaks down to 64
proposals for directives and 61 proposals for regulations. Our next steps were a) a
thorough media analysis of all these proposals and b) interviewing projects with experts
in the EC, the EP and interest group officials. The interviewing projects took the set of
125 cases as a starting point.
Table 1 around here
Via an online search in the electronic archives of five media outlets (European
Voice, EurActiv, Agence Europe, Le Monde and Financial Times) we mapped the complete
media coverage related to the 125 legislative cases. Important is that only coverage that
could be directly connected to the EC proposal was kept; coverage that was only vaguely
related to the subject matter of the proposal was not archived. We adopted this rather
strict rule as we wanted to concentrate on coverage related to legislative issues, and not
necessarily the coverage on some more general theme indirectly or vaguely related to
the legislative case. In a next step we identified all stakeholders (public and private) and
stored all the statements these actors made in a separate database. Statements are
quotes made by interest group officials (for instance in an interview with a journalist)
that can be directly linked to one of the sampled proposals (all these statements were
coded as well; see De Bruycker & Beyers 2014). This part of the mapping implies that we
can make a distinction between actors that are only vaguely mentioned (n=288) from
those that actively contribute to some media debate (n=379).
17
For each of the 125 sampled pieces of legislation the responsible policy unit and
policy expert from the Commission was identified and invited for an expert interview.10
In 29 cases potential respondents refused to be interviewed or officials argued that they
did not remember enough about the specific case. For 26 cases very short preliminary
interviews took place, sometimes over the phone, which showed that no or very little
lobbying took place. In the end, this led to 70 legislative cases for which lobbying was
confirmed and extensive face-to-face interviews with EC-experts were conducted.
During these interviews, the expert was asked to list all relevant stakeholders that were
actively involved in the specific legislative case, and to identify key issues, the main
conflict dimensions and policy positions that stakeholders had adopted. In this way we
identified 658 interest groups. In the next stage of the interview project, following the
interviews with 95 EC-experts, we conducted 141 interviews with interest group
officials. In the selection of respondents we relied on evidence collected through the
media analysis and the EC-expert interviews. One important part of the interview
consisted of a detailed screening and characterization of all the actors (for instance
identifying who was very active, who were coalitions leaders, important providers of
expertise) we identified in the previous steps, plus adding actors that remained
unidentified. The interviews with group officials started with the 70 proposals on which
EC-expert interviews took place, but we added 15 proposals where we encountered
considerable media attention in terms of interest groups that made public statements on
this case. In this way we identified an additional set of 291 organizations.
Data collection
Interest groups from the EP register as well as the groups that were identified
10
This work was largely conducted by the Austrian INTEREURO team.
18
through the top-down mapping were coded on a number of different variables (see
codebook www.intereuro.be). Information was coded mainly on the basis of
organizations’ websites, and, sometimes, also on the basis of annual reports, information
submitted to the transparency register, and other sources of publicly available
information. Several student-coders collected the data under supervision of a postdoctoral researcher. They were trained in three distinct groups of four students, held
regular meetings to cross-verify the treatment of specific cases and inter-coder
reliability checks were satisfactory.
The key benefit of our reliance on online, publicly available sources rather than
surveys is that it provides us with a very high ‘response rate’. Only a very small
proportion of defunct or marginal organizations could not be found online. Our
approach does not suffer from major selection bias, as may to a certain extent be the
case for survey research, and to a lesser extent face-to-face interviews.
Yet there are a couple of limitations associated with the use of website
information. First, , we face problems of missing data, in particular for variables
measuring organizational resources and staff size the response rate is much lower than
fifty percent. And even for those organizations where we found information on staff size,
it is surely impossible to differentiate, on the basis of organizational websites, between
‘lobby’ staff and other staff. This validity problem leads us to disregard this part of the
data collected. Second, actual, offline policy-oriented activities of organizations is
sometimes poorly presented. This makes it very difficult to validly identify the policy
interests of organizations. For that reason we refrained from classifying organizations
into the main categories of the Policy Agendas Project (see: comparativeagendas.org),
although this is a relatively common type of data collection strategy is such research
projects (e.g. Jordan et al. 2012; Johnson 2013). Much of this information could be
19
obtained through interviews with the ‘top-down’ sample, but as this type of data is
lacking for the whole population we will not use it for this paper. For each of the
variables presented below, these validity problems do not occur or are not so severe.
For this paper we rely on our coding of the governance level at which an
organization is mobilized, their organization structures, the geographic location of their
headquarters, the organizational form, and either the economic or social sector from
which they are drawn.
Empirical Analysis
It is clear from Figure 1 that the top-down sampling of organized interests active
on EU-legislative processes identifies many organizations not included in what is the
most comprehensive available bottom-up census of those lobbying in Brussels. While
the top down sample consists of 935 organizations, 588 (or 63 percent) are not part of
the bottom-up population. Moreover, only 347 appear in both interest populations,
which constitutes 37 percent of the top-down population and only 15 percent of the
bottom-up population. There are many potential reasons for this. Most prominently,
both types of mapping strategies are incomplete. Top-down sampling may pick-up
organizations, for instance through media reports, that do not actually lobby. Even
experts may under- or overestimate the lobbying activities of some organizations and
any bottom-up population census is likely to be incomplete.11 We will discuss these
reasons and others much more thoroughly in the conclusion. For now, however, it is
worth adding these sampling problems to the list of more substantive reasons why
11
Even the quite rigorous lobby registration of the U.S. national government under the Lobby Disclosure
Act of 1993 is incomplete via exclusion of organizations spending less than a fixed dollar threshold, those
that lobby only via the media, and those active only in electoral campaigns via PACs. This problem is even
more sever in the EU where we lack a rigorous registration system and where, due to the multi-layered
system of the EU, boundaries of the interest groups system are even more difficult to draw.
20
bottom-up and top-down mapping strategies may generate different distributions of
interest organizations.
Figure 1 about here
We compare the distributions of interests generated by the two INTEREURO
sampling strategies, as well as the individual cases they identify, across six variables
generated for both: the level of mobilization of the organization, their organization
structures, the geographic location of their headquarters, the type of actor they are, and
either the economic or social sector from which they are drawn. We will not say much
about the individual values of these variables, although these will be apparent in our
discussion of the data, since the issue here is not measurement validity per se, but the
comparability of their values across two different sampling strategies. Nonetheless,
these variables are of long-standing concern in both the literature on organized interests
and among those concerned about interest representation in the EU. We should note,
however, that not all interest organizations were coded on the last two variables: the
ISIC codes of economic organizations and the social codes for organizations lacking an
ISIC code; all organizations were coded by one or the other of the variables. We will also
compare the balance of these two different types of organizations across the two
mapping strategies in the INTEREURO dataset.
To assess the comparability of the data generated by the two samples, we first
examine the overall distributions of the six variables. The full tables on these
distributions are presented in appendixes 1 through 6 where the five pairs of columns
present frequencies of the six tables for five subsets of the total dataset – 1.) the cases
uniquely generated by the bottom-up sample (not recorded in the top-down sample), 2.)
21
the cases included in the total bottom-up sample, 3.) all cases identified by both
mapping strategies (after eliminating duplicates), 4.) the cases included in the total topdown sample, and 5.) the cases uniquely identified by the top-down sample (not
recorded in the bottom-up sample).12 Frequency distributions drawn from these tables
are presented in Figures 2 through 7 for the same five sets of cases.
Figure 2-7 about here
There are some differences evident across the distributions generated by the
mapping strategies. These are perhaps best evident via comparing the second and fourth
bars of the figures – to total bottom-up and total top-down datasets, respectively,
recognizing that these include some of the same interest organizations. In Figure 2 on
level of mobilization, for example, non-EU multinationals are somewhat better
represented in the bottom-up sample (37.40 percent) than in the top-down sample
(31.53) percent, suggesting that they are more passive or are more likely to restrict their
activities to policy monitoring only (and to not lobby that many legislative cases). In
figure 4 on the geographic headquarters of interest organizations, U.S. and Canadian
interests are less well represented in the total bottom-up sample (6.24 percent)
compared to the top-down sample (12.55), the reverse of what is found for Belgianheadquartered interests – 29.35 and 22.64 percent, respectively. In Figure 6 on the ISIC
codes for economic sector, finance, insurance, and real estate interests are less well
represented in the total bottom-up sample (7.77 percent) compared to the top-down
sample (21.50). In Figure 7 on the social codes for interest organizations lacking an ISIC
code, employer and producer groups interests are less well represented in the total
12
The numbers of observations in the appendices tables differ among each other because of unique sets of
missing values on the six variables.
22
bottom-up sample (38.69 percent) compared to the top-down sample (49.52), the same
that is true of environmental interests – 9.95 and 18.33 percent, respectively. Thus, the
two mapping strategies do not generate precisely the same distributions of interests
across the six variables.
Figure 8 about here
At the same time, however, the primary message of Figures 2 through 7 is that
these distributions of interests generated by the two mapping strategies are remarkably
similar in their overall distributions. This is evident in Figure 8, which presents
correlation coefficients for the distributions in the second and fourth columns of Figures
2 through 7. All of the coefficients are 0.942 or higher except for the distributions for
the primary social code of economic organizations, which was 0.800 (see also De
Bruycker & Beyers 2014). Another way to see this overall similarity is in terms of what
is perhaps the primary concern of scholars concerned about interest system diversity
and bias – the balance of economic and social organizations. As noted earlier, interest
organizations were coded either by an ISIC code (Figure 6) or a social code for
organizations lacking an ISIC code (Figure 7). In the total bottom-up sample, 68.85
percent of the cases were assigned an ISIC-code, nearly identical to the 69.83 percent
that were so assigned in the total top-down sample. Conversely, 31.15 percent of the
cases in the total bottom-up sample were assigned a social code, which is quite similar
to the 30.17 percent so assigned in the total top-down sample.13 Thus, despite our
expectations of sharp differences in the tallies of interest organizations across the two
mapping strategies, it seems as if the list of organizations most active on major policy
13
While we label those lacking an ISIC code social groups, such organizations, as is evident in our
discussion of figure 7, do include economic organizations, most notably employer and producer groups.
23
issues in the EU (the top-down sample) appears not especially dissimilar from what
might be generated from a random sample of all of the interest organizations lobbying
the EU as generated via the best available bottom-up sample of EU interest
organizations.
While the distributions of the bottom-up and top-down mapping efforts across
the six variables of interest are quite similar, do they tally the same individual
organizations? This is certainly not the case as was evident in figure 1; the top-down
sample of organizations was not fully nested in the bottom-up population census. This
is typical across the six variables we have examined as well, as seen in appendix 7.14 The
most telling issue here concerns how many of the organizations tapped by the top-down
sample of those actively lobbying of the prominent issues before the EU were included
in the bottom-up census of the population of interest lobbying the EU. These
proportions are reported in figure 9 for the six variables of interest. The majority of the
lists of interest organizations tallied by the top-down mapping of those active in
lobbying the prominent issues before the EU were also included in the bottom-up census
of all organizations active in lobbying the EU for only one of the six variables of interest:
he primary social coding variable (52.381 percent). On all of the other variables, a
majority of cases were not included in the bottom-up sample.
Conclusion
This leaves us with something of a puzzle. It seems the distributions of the
observations generated by bottom-up and top-down mapping procedures generate
quite similar distributions on our six variables. This is good news for scholars studying
14
Again, the number of observations in the this table differ from each other and that reported for figure 1
due to missing data on the individual variables.
24
the politics of interest representation in that we should feel more free to generalize
about broader mobilization issues using data generated from sample of interest
organizations active on major policy issues. One important condition is, however, that
scholars are conscious about the various potential sources of bias and variation when
they design studies with bottom-up and top-down samples. And we should feel more
willing to employ bottom-up population-level data in analyzing research questions
related to the relative influence of different kinds of interests on specific policy issues.
At the same time, however, we have seen that the two mapping strategies do not
capture the same individual organizations. More specifically, the top-down sample of
organizations is not subsumed by the bottom-up census of interest organizations
generated through the bottom-up mapping procedure. This means that we have to
remain careful and cannot unambiguously attribute any observed influence effects to
specific constellations of interest organizations when using bottom-up data to identify
the relative strengths of different types of competing interest organizations. In
particular it is important to consider why small fluctuations emerge due to some policy
agenda effects (e.g. the large number of banking and financial interests).
The most likely explanation for why the organizations identified by the top-down
mapping process are not fully captured by the bottom-up census lies in the inherent
inadequacies of both types of samples. This implies, of course, that their combination,
while excluding duplicate entries, is a useful approach to addressing their inadequacies,
although only the INTEREURO project has been able to combine and compare both
mapping strategies to date. The inadequacies of the bottom-up mapping process are
more obvious than those of the top-down strategy. Simply put, the EU does not have
anything like a comprehensive and rigorous registration system. Moreover, the multilayered structure and transnational nature of the EU makes that the boundaries of its
25
interest group system are difficult to establish. The door pass data we have used in the
INTEREURO project is, we believe, the best, most comprehensive data now available.
But it is incomplete. In particular, it is less likely than a full registration system that
tallies lobbying in all EU institutions – as is done under the Lobbying Disclosure Act of
1993 in the U.S – would be to capture influence at the earlier agenda-setting stage of the
policy process, which is likely to be centered on the EC. And quite simply, those active at
that stage may not be active at later stages of the policy process that include decisions
taken in the EP and the Council. In particular, advocates that support the Commission
and that face strong opposition in the EP and/or the Council might be reluctant to put
much pressure on policymakers in the EP as this may simply attract the attention of
their opponents.
At the same time, however, the top-down procedure might capture interest
organizations that do not very actively lobby on specific policy proposals or that for
whom lobbying on a particular issue is not their core business. This is good news as it
implies that top-down mapping might be much less sensitive to influence and
mobilization bias than usually expected. One of the reasons is that one of the key sources
of information on lobbying in the top-down mapping process entails using media
reports to identify organizations with interests in a particular proposal. Using media
reports for this purpose is not uncommon in studies of the influence of interest
organizations (Andrews & Caren 2010; Barker-Plummer 2002; Bernhagen & Trani
2012; Binderkrantz 2012; Danielian 1994; De Bruycker & Beyers 2014). Yet, the media
might well cite an organization as an example of how a particular proposal might bear
on the activities of those it is trying to influence without that organization actually
lobbying on the proposal. Also, an organization might comment on a proposal without it
then doing anything substantive to influence its fate. Another reason is that a top-down
26
mapping, if conducted properly, results in a varying mix of highly prominent cases on
which a large number of organizations are lobbying and a set of much less prominent
cases where only a handful lobbyists are active. Many of the organizations identified in
such a way are ‘followers’ who jump on the bandwagon that is led by a rather small set
of leading organizations. Being part of the pack is crucial for generating necessary
visibility and resources.
27
References
Anderson, Jennifer, Adam Newmark, Virginia Gray, and David Lowery. 2004. “Mayflies
and Old Bulls: Demographic Volatility and Experience in State Interest
Communities,” State Politics and Policy Quarterly, 4 (2): 140-160.
Andrews, K. T., & Caren, N. 2010. “Making the News Movement Organizations, Media
Attention, and the Public Agenda.” American Sociological Review, 75, 841-866.
Balme, Richard & Didier Chabanet. 2008. European Governance and Democracy: Power
and Protest in the EU. Lanham, MD: Rowman & Littlefield,.
Barker-Plummer, B. 2002. “Producing public voice: Resource mobilization and media
access in the National Organization for Women.” Journalism & Mass
Communication Quarterly. 79: 188-205.
Baumgartner, Frank F. & Beth L. Leech. 1998. Basic Interests: The Importance of Groups
in Politics and in Political Science. Princeton: Princeton University Press.
Baumgartner, Frank R. and Beth L. Leech. 2001. “Interest Niches and Policy
Bandwagons: Patterns of Interest Group Involvement in National Politics.”
Journal of Politics. 63: 1468-2508.
Baumgartner, Frank R., Jeffrey M. Berry, Marie Hojnacki, David C. Kimball, and Beth L.
Leech. 2009. Lobbying and Policy Change. Chicago: University of Chicago Press.
Berkhout, Joost and David Lowery. 2011. “Short-Term Volatility in the EU Interest
Community.” Journal of European Public Policy. 18 (1): 1-16.
Berkhout, Joost. 2010. Political Activities of Interest Organizations: Conflicting Interests,
Converging Strategies. Mostert and van Onderen: Leiden.
Bernhagen, P., and Trani, B. 2012. “Interest group mobilization and lobbying patterns in
Britain: A newspaper analysis.” Interest groups & Advocacy. 1: 48-66.
Beyers, J., A. Duer, D. Marshall and A. Wonka. 2014b. “Policy-Centred Sampling in
28
Interest Group Research: Lessons from the INTEREURO-project.” Interest Groups
& Advocacy. 3: 160-173.
Beyers, J., C. Braun, D. Marshall and I. De Bruycker. 2014c. “Let’s talk! On the practice
and method of interviewing policy experts.” Interest Groups & Advocacy. 3: 174187.
Beyers, J., R. Eising and W. Maloney. 2008. “Researching Interest Group Politics in
Europe and Elsewhere: Much We Study, Little We Know?” West European
Politics. 31: 1103-1128.
Beyers, Jan, Laura Chaques Bonafant, Andreas Dur, Rainer Eising, Danica Fink-Hafner,
David Lowery, Christine Mahoney, William Maloney, and Daniel Naurin. In 2014a.
“The INTEREURO Project: Logic and Structure.” Interest Groups and Advocacy. 3
(2): 126-140.
Binderkrantz, Anne S. 2012. “Interest groups in the media: Bias and diversity over time.”
European Journal of Political Research. 51: 117-139.
Binderkrantz, Anne S., Peter M. Christiansen & Helene H. Pedersen. 2014. “Interest
Group Access to the Bureaucracy, Parliament, and the Media.” Governance.
DOI: 10.1111/gove.12089
Bunea, A. and F. R. Baumgartner. 2014. “The state of the discipline: authorship, research
designs, and citation patterns in studies of EU interest groups and lobbying.”
Journal of European Public Policy. doi: 10.1080/13501763.2014.936483.
Danielian, L.H., & Page, B.I. 1994. “The heavenly chorus: Interest group voices on TV
news.” American Journal of Political Science. 38: 1056-1078.
De Bruycker, Iskander and Jan Beyers. 2014. “Balanced or Biased? Interest Groups and
Legislative Lobbying in the European News Media.” Political Communication.
forthcoming.
29
Dür, Andreas and Gemma Mateo. 2013. “Gaining Access Or Going Public? Interest Group
Strategies in Five European Countries.” European Journal of Political Research.
52: 660-686.
Gray, Virginia and David Lowery. 1996. The Population Ecology of Interest
Representation: Lobbying Communities in the American States. Ann Arbor,
Michigan: University of Michigan Press.
Gray, Virginia, David Lowery, and Jennifer Benz. 2013. Organized Interests and Health
Policy in the American States. Washington D.C: Georgetown University Press.
Greenwood, J. and J Dreger. 2013. “The Transparency Register: A European Vanguard of
Strong Lobby Regulation Quest.” Interest Groups & Advocacy. 2: 139-162.
Halpin, Darren and Anna S. Binderkrantz. 2011 “Explaining Breadth of Policy
Engagement: Patterns of Interest Group Mobilization in Public Policy.” Journal of
European Public Policy. 8 (2): 201-219.
Halpin, Darren and Grant Jordan. 2012. “Estimating Group and Associational
Populations: Endemic Problems but Encouraging Progress.” In Halpin, Darren
and Grant Jordan (eds.) The Scale of Interest Organization in Democratic Politics:
Data and Research Methods. Palgrave Macmillan, Basingstoke.
Halpin, Darren, Baxter, G. & MacLeod, I. 2011. “Multiple Arenas, Multiple Populations:
Counting Organized Interests in Scottish Public Policy.” In Halpin, Darren and
Grant Jordan (eds.) The Scale of Interest Organization in Democratic Politics: Data
and Research Methods. Palgrave Macmillan, Basingstoke.
Halpin, Darren. 2011. “Explaining Policy Bandwagons: Organized Interest Mobilization
and Cascades of Attention.” Governance, 24: 205-230.
Hanagraaff, Marcel. 2014. All the World’s a Stage: Interest Group Politics at WTO and
UNFCC Negotiating Conferences. Antwerp: University of Antwerp.
30
Hanegraaff, Marcel, Jan Beyers and Iskander De Brucyker. 2014. "In Front or Behind the
Scene? The Political Strategies of Lobbyists at Global Diplomatic Conferences."
under review.
Heinz, John P., Edward O. Laumann, Robert L. Nelson, and Robert Salisbury. 1993. The
Hollow Core. Cambridge, Massachusetts: Harvard University Press.
Jentges, Eric, Matthias Brändli, Patrick Donges, and Offried Jarren. 2012. “Die
Kommunikation Politischer Interessengruppen in Deutschland: Adressaten,
Instrumente Und Logiken.” Studies in Communication|Media. 3/4: 281-409.
Johnson, E.W. 2013. “Toward International Comparative Research on Associational
Activity: Variation in the Form and Focus of Voluntary Associations in Four
Nations.” Nonprofit and Voluntary Sector Quarterly. 43: 163S-181S.
Jordan, Grant, Darren Halpin & William Maloney. 2004. “Defining Interests:
Disambiguation and the Need for New Distinctions.” British Journal of Political
Science. 6: 195-212.
Jordan, Grant, Frank Baumgartner, John, McCarthy, Shaun Bevan, and Jamie Greenan.
2012. “Tracking Interest Group Populations in the US and the UK.” In Halpin,
Darren and Grant Jordan (eds.) The Scale of Interest Organization in Democratic
Politics: Data and Research Methods. Palgrave Macmillan, Basingstoke.
Klüver, Heike, Christine Mahoney and Mark Opper. 2014. “Framing in context: How
interest groups frame policy debates in the European Union.” under review.
Klüver, Heike: Citizens, interest groups and legislative activity: A longitudinal study of
issue evolution in Germany, unpublished manuscript
Klüver, Heike. 2013. Lobbying in the European Union: Interest Groups, Lobbying
Coalitions and Policy Change. Oxford: Oxford University Press.
Leech, Beth L., Frank R. Baumgartner, Timothy La Pira, and Nicholas A. Semanko. 2005.
31
“Drawing Lobbyists to Washington: Government Activity and the Demand for
Advocacy.” Journal of Politics. 58: 19-30.
Lowery, David and Virginia Gray. 2004. “A neopluralist perspective on research on
organized interests.” Political Research Quarterly. 57: 164-175.
Lowery, David. 2007. “Why Do Organized Interests Lobby? A Multi-Goal, Multi-Context
Theory of Lobbying.” Polity. 39 (1): 29-54.
Mahoney, Christine. 2008. Brussels Versus the Beltway: Advocacy in the United State
and the European Union. Washington, D.C.: Georgetown University Press.
Salisbury, R.H. (1994) Interest Structures and Policy Domains: A Focus for Research.
Crotty, W.J., M.A. Schwartz and J.C. Green (eds) Representing Interests and Interest
Group Registration. , University Press of America Washington, DC: 12-20.
Schattschneider, E. E. 1960. The Semisovereign People. New York: Holt, Rinehart, and
Winston.
Schlozman, Kay Lehman, Sidney Verba, and Henry E. Brady. 2012. The Unheavenly
Chorus: Unequal Political Voice and the Broken Promise of American Democracy.
Princeton: Princeton University Press.
Sorurbakhsh, Laila. 2014. “Population Ecology and European Interest Groups Over
Time.” European Political Science .13: 61-77.
Thrall, A.T. 2006. “The Myth of the Outside Strategy: Mass Media News Coverage of
Interest Groups.” Political Communication. 23: 407-420.
Toshkov, Dimiter, David Lowery, Brendan Carroll, and Joost Berkhout. 2013. “Timing is
Everything? Organized Interests and the Timing of Legislative Activity.” Interest
Groups and Advocacy. 2 (1): 48-70.
Walker, Jack L. 1991. Mobilizing Interest Groups in America. Ann Arbor Michigan:
University of Michigan Press.
32
Webb, Susan. 2006. “Sweet-Talking the Fourth Branch: Assessing the Influence of
Interest Group Comments on Federal Agency Rulemaking.” Journal of Public
Administration Research and Theory. 26: 103-124.
Witko, Christopher. In Press. “Case Study Approaches to Studying Organization Survival
and Adaptation.” In David Lowery, Darren Halpin, and Virginia Gray, eds. The
Organizational Ecology of Interest Communities Reconsidered. Palgrave
Macmillan, Basingstoke.
Wonka, Arndt, Frank R. Baumgartner, Christine Mahoney, and Joost Berkhout. 2010.
“Measuring the Size and Scope of the European Union Interest Group Population.”
European Union Politics. 11: 463-476.
33
Table 1. Number of groups identified in EC-expert interviews, media
sources and interest group interviews
N legislative
proposals
Total number of
groups identified
95 EC-expert
interviews
Media sources;
mentions
Media sources;
statements
Total number
identified
125
In 141 Interest
group
interviews
85
70
125
658
288
379
291
1496
Figure 1. Venn-diagram bottum-up and top-down populations
Venn-diagram (N=2895)
Bottum-up population
N=1960 (68%)
Overlap
N=347 (12%)
Top-down population
N=588 (20%)
34
35
36
37
38
39
40
41
42
43